Amazon Web Services, every mention
19 scenes (2023) · ← back to Amazon Web Services
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every year 2023 anyone Alex Kantrowitz 111Matt Wood 20Matt Garman 7Ranjan Roy 5Bill Vass 5M.G. Siegler 4Stephen Morris 2Stephanie Link 2Sridhar Ramaswamy 2Snehal Antani 2
Verbatim, from the transcripts: the passages where Amazon Web Services comes up
How Generative AI Is Changing Travel — With Priceline's Marty Brodbeck
- ▶ 23:43 Marty Brodbeck Well, I think in general, you know, the, the startup community, uh, AWS, OpenAI, Microsoft, and Google, they're all doing phenomenal jobs in terms of producing meaningful products that companies like Priceline can, can benefit from. 2 times in the scene
AI Keynote: Six Bold Predictions About The Future Of Artificial Intelligence
- ▶ 8:55 Alex Kantrowitz What I want is for you to work on Amazon Web Services. 3 times in the scene
Big Technology's New Release, AI Bubble Looms, Apple's Next Event — With Brian McCullough
- ▶ 13:33 Alex Kantrowitz And while doing this, they've sort of, and Matt Wood was, uh, the, this VP from AWS was on the show. 4 times in the scene
A Dozen Grueling Years At Amazon — With Kristi Coulter
- ▶ 4:24 Kristi Coulter There was no web services. 2 times in the scene
Amazon Reveals Its AI Master Plan — With Matt Wood
- ▶ 0:12 Alex Kantrowitz Okay, you're dabbling that in that area, in those areas, but I don't know if you stand out there yet, but where you are really trying to compete is in this space where companies, the big companies bring their models inside AWS, and then… 2 times in the scene
- ▶ 3:14 Alex Kantrowitz We'd like to make it available to your clients through AWS.
- ▶ 7:03 Matt Wood And so one of the things we're adding to bedrock is the ability to be able to provide that information to the language model, uh, using your own private data, uh, inside the applications that are already run in the Amazon cloud. 2 times in the scene
- ▶ 9:34 Matt Wood And to be able to leverage the investments that they've already made in that data on AWS using completely novel capabilities in addition to existing models and novel models as well.
- ▶ 11:31 Matt Wood You'd be surprised how many customers have exabytes of data on AWS, and they can take that data that they've invested in, and they can use it with these models to create a net new asset for their organization. 2 times in the scene
- ▶ 18:24 Matt Wood AI part of, um, our cloud computing business was larger than the rest of AWS combined in a couple years.
- ▶ 20:05 Alex Kantrowitz Now, it wasn't everybody going at the same time, and you were very early in AWS, so you know this, but AWS kind of ran away with the cloud computing field or cloud services field. 4 times in the scene
- ▶ 21:34 Alex Kantrowitz So I'd like to hear a little bit more about like the practical level of, and maybe you can go step by step of like what, and briefly, but like what people would build with the AWS services. 2 times in the scene
- ▶ 26:41 Matt Wood On AWS, and then use a machine learning algorithm to build their own chatbot, which is Bloomberg GPT, and they ran all of that inside our, um, cloud computing infrastructure. 2 times in the scene
- ▶ 30:03 Matt Wood And so that, that is a huge investment that we've been making at AWS for nearly a decade now.
- ▶ 30:54 Alex Kantrowitz He's a VP of product at AWS, focused on AI.
- ▶ 36:36 Matt Wood I like a lot of our customers at AWS, and it is inspiring.
- ▶ 37:54 Alex Kantrowitz Is it AWS learning from the rest of the workflow inside Amazon, or people inside Amazon learning from AWS? 2 times in the scene
- ▶ 40:41 Matt Wood And the, ah, machine learning work use cases very quickly rose to the top, and so we've been investing there in terms of building out custom silicon that you can deploy on AWS today,
- ▶ 46:07 Alex Kantrowitz The point of the book is that the company operates as if it's a startup on its first day, and the culture has been extremely intentionally built that way by Bezos, and there was a story recently about how Amazon has more of a big company…